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Yenilenebilir Enerji Kaynakları İçin Dijital İkiz Konsepti

Year 2021, Volume: 9 Issue: 3, 836 - 844, 01.09.2021
https://doi.org/10.36306/konjes.969989

Abstract

Bu çalışmada; mevcut enerji kaynaklarına alternatif niteliğinde olan ve diğer alternatif enerji kaynaklarına oranla en büyük paya sahip rüzgar ve güneş enerji sistemleri üzerine dijital ikiz konseptinin nasıl adapte edilebileceği hakkında araştırmalar yapılmıştır. Günümüzde popüler çalışma konularından biri olan dijital ikiz konseptinin bu enerji kaynaklarına ne gibi faydalar sağlayabileceği üzerine öngörülerde bulunulmuştur. Bu amaçla öncelikli olarak dijital ikiz konsepti tanıtılmış ve günümüzdeki uygulamaları hakkında bilgiler verilmiştir. Daha sonra çalışma kapsamında önerilen şekli ile dijital ikiz konseptinin alternatif enerji kaynaklarına nasıl adapte edilebileceği hakkında bilgiler verilmiştir. Ek olarak yenilenebilir/alternatif enerji kaynakları alanında yapılan akademik çalışmalar incelenmiş ve elde edilen bulgular üzerinde değerlendirmeler yapılmıştır.

References

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  • Arafet, K., & Berlanga, R. (2021). "Digital Twins in Solar Farms: An Approach through Time Series and Deep Learning", Algorithms, 14(5). doi: ARTN 15610.3390/a14050156
  • Bartsch, K., Pettke, A., Hubert, A., Lakamper, J., & Lange, F. (2021). "On the digital twin application and the role of artificial intelligence in additive manufacturing: a systematic review", Journal of Physics-Materials, 4(3). doi: ARTN 03200510.1088/2515-7639/abf3cf
  • Bhatti, G., Mohan, H., & Singh, R. R. (2021). "Towards the future of smart electric vehicles: Digital twin technology", Renewable & Sustainable Energy Reviews, 141. doi:ARTN 11080110.1016/j.rser.2021.110801
  • Cai, H. X., Zhu, J. M., & Zhang, W. (2021). "Quality Deviation Control for Aircraft Using Digital Twin", Journal of Computing and Information Science in Engineering, 21(3). doi:Artn031008
  • Çetinkaya, N. (2017). "Improving of renewable energy support policy and a performance analysis of a grid connected 1 MWP PV power plant in Konya", Selçuk Üniversitesi Mühendislik, Bilim ve Teknoloji Dergisi, 5(3), 251-261.10.1115/1.4050376
  • Darbali-Zamora, R., Johnson, J., Summers, A., Jones, C. B., Hansen, C., & Showalter, C. (2021). "State Estimation Based Distributed Energy Resource Optimization for Distribution Voltage Regulation in Telemetry-Sparse Environments Using a Real-Time Digital Twin", Energies, 14(3). doi: ARTN 77410.3390/en14030774
  • Dhimish, M. (2021). "Defining the best-fit machine learning classifier to early diagnose photovoltaic solar cells hot spots", Case Studies in Thermal Engineering, 25. doi: ARTN 10098010.1016/j.csite.2021.100980
  • Jain, P., Poon, J., Singh, J. P., Spanos, C., Sanders, S. R., & Panda, S. K. (2020). "A Digital Twin Approach for Fault Diagnosis in Distributed Photovoltaic Systems", Ieee Transactions on Power Electronics, 35(1), 940-956. doi: 10.1109/Tpel.2019.2911594
  • Juarez, M. G., Botti, V. J., & Giret, A. S. (2021). "Digital Twins: Review and Challenges", Journal of Computing and Information Science in Engineering, 21(3). doi: Artn 03080210.1115/1.4050244
  • Kolantla, D., Mikkili, S., Pendem, S. R., & Desai, A. A. (2020). "Critical review on various inverter topologies for PV system architectures", Iet Renewable Power Generation, 14(17), 3418-3438. doi: 10.1049/iet-rpg.2020.0317
  • Kritzinger, W., Karner, M., Traar, G., Henjes, J., & Sihn, W. (2018). "Digital Twin in manufacturing: A categorical literature review and classification", Ifac Papersonline, 51(11), 1016-1022. doi: 10.1016/j.ifacol.2018.08.474
  • Lattanzi, L., Raffaeli, R., Peruzzini, M., & Pellicciari, M. (2021). "Digital twin for smart manufacturing: a review of concepts towards a practical industrial implementation", International Journal of Computer Integrated Manufacturing. doi: 10.1080/0951192x.2021.1911003
  • Lim, K. Y. H., Zheng, P., & Chen, C. H. (2020). "A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives", Journal of Intelligent Manufacturing, 31(6), 1313-1337. doi: 10.1007/s10845-019-01512-w
  • Liu, M. N., Fang, S. L., Dong, H. Y., & Xu, C. Z. (2021). "Review of digital twin about concepts, technologies, and industrial applications", Journal of Manufacturing Systems, 58, 346-361. doi: 10.1016/j.jmsy.2020.06.017
  • Lu, Y. L., Huang, X. H., Zhang, K., Maharjan, S., & Zhang, Y. (2021). "Communication-Efficient Federated Learning for Digital Twin Edge Networks in Industrial IoT", Ieee Transactions on Industrial Informatics, 17(8), 5709-5718. doi: 10.1109/Tii.2020.3010798
  • Moghadam, F. K., Reboucas, G. F. D., & Nejad, A. R. (2021). "Digital twin modeling for predictive maintenance of gearboxes in floating offshore wind turbine drivetrains", Forschung Im Ingenieurwesen-Engineering Research, 85(2), 273-286. doi: 10.1007/s10010-021-00468-9
  • Nguyen, V. H., Tran, Q. T., Besanger, Y., Jung, M., & Nguyen, T. L. (2021). "Digital twin integrated power hardware-in-the-loop for the assessment of distributed renewable energy resources", Electrical Engineering. doi: 10.1007/s00202-021-01246-0
  • ÖKSEL, C., Ali, K. O. Ç., Yıldız, K. O. Ç., & YAĞLI, H. (2016). "Off-shore Wind Energy Potential Research for Antakya Bay", Selçuk Üniversitesi Mühendislik, Bilim ve Teknoloji Dergisi, 4(1), 18-29.
  • Peng, Y. Z., Zhao, S., & Wang, H. (2021). "A Digital Twin Based Estimation Method for Health Indicators of DC DC Converters", Ieee Transactions on Power Electronics, 36(2), 2105-2118. doi: 10.1109/Tpel.2020.3009600
  • Rassolkin, A., Orosz, T., Demidova, G. L., Kuts, V., Rjabtsikov, V., Vaimann, T., & Kallaste, A. (2021). "Implementation of Digital Twins for electrical energy conversion systems in selected case studies", Proceedings of the Estonian Academy of Sciences, 70(1), 19-39. doi: 10.3176/proc.2021.1.03
  • Schroeder, G. N., Steinmetz, C., Rodrigues, R. N., Henriques, R. V. B., Rettberg, A., & Pereira, C. E. (2021). "A Methodology for Digital Twin Modeling and Deployment for Industry 4.0", Proceedings of the Ieee, 109(4), 556-567. doi: 10.1109/Jproc.2020.3032444
  • Sjarov, M., Lechler, T., Fuchs, J., Brossog, M., Selmaier, A., Faltus, F., Franke, J. (2020). "The Digital Twin Concept in Industry - A Review and Systematization", 2020 25th Ieee International Conference on Emerging Technologies and Factory Automation (Etfa), 1789-1796.
  • Sun, W., Lei, S. Y., Wang, L., Liu, Z. Q., & Zhang, Y. (2021). "Adaptive Federated Learning and Digital Twin for Industrial Internet of Things", Ieee Transactions on Industrial Informatics, 17(8), 5605- 5614. doi: 10.1109/Tii.2020.3034674
  • Uzum, B., Onen, A., Hasanien, H. M., & Muyeen, S. M. (2021). "Rooftop Solar PV Penetration Impacts on Distribution Network and Further Growth Factors-A Comprehensive Review", Electronics, 10(1). doi: ARTN 5510.3390/electronics10010055
  • Wang, M. M., Wang, C. Y., Hnydiuk-Stefan, A., Feng, S. Z., Atilla, I., & Li, Z. (2021). "Recent progress on reliability analysis of offshore wind turbine support structures considering digital twin solutions.", Ocean Engineering, 232. doi: ARTN 10916810.1016/j.oceaneng.2021.109168
  • Zohdi, T. I. (2021). "A digital-twin and machine-learning framework for the design of multiobjective agrophotovoltaic solar farms.", Computational Mechanics. doi:10.1007/s00466-021-02035-z

DIGITAL TWIN CONCEPT FOR RENEWABLE ENERGY SOURCES

Year 2021, Volume: 9 Issue: 3, 836 - 844, 01.09.2021
https://doi.org/10.36306/konjes.969989

Abstract

In this study, research has been conducted on how to adapt the digital twin concept on wind and solar energy systems, which are alternatives to existing energy sources and have the largest share compared to other alternative energy sources. Predictions have been made on possible benefits provided to these energy sources by the digital twin concept, which is one of the popular study topics today. For this purpose, firstly, the concept of the digital twin is introduced and information about its recent applications is given. Then, information is given about how the digital twin concept can be adapted to alternative energy sources, as suggested within the scope of the study. In addition, academic studies in the field of renewable/alternative energy resources are examined and evaluations are made on the findings.

References

  • An, J., Chua, C. K., & Mironov, V. (2021). "Application of Machine Learning in 3D Bioprinting: Focus on Development of Big Data and Digital Twin", International Journal of Bioprinting, 7(1), 1-6. doi: ARTN 34210.18063/ijb.v7i1.342
  • Arafet, K., & Berlanga, R. (2021). "Digital Twins in Solar Farms: An Approach through Time Series and Deep Learning", Algorithms, 14(5). doi: ARTN 15610.3390/a14050156
  • Bartsch, K., Pettke, A., Hubert, A., Lakamper, J., & Lange, F. (2021). "On the digital twin application and the role of artificial intelligence in additive manufacturing: a systematic review", Journal of Physics-Materials, 4(3). doi: ARTN 03200510.1088/2515-7639/abf3cf
  • Bhatti, G., Mohan, H., & Singh, R. R. (2021). "Towards the future of smart electric vehicles: Digital twin technology", Renewable & Sustainable Energy Reviews, 141. doi:ARTN 11080110.1016/j.rser.2021.110801
  • Cai, H. X., Zhu, J. M., & Zhang, W. (2021). "Quality Deviation Control for Aircraft Using Digital Twin", Journal of Computing and Information Science in Engineering, 21(3). doi:Artn031008
  • Çetinkaya, N. (2017). "Improving of renewable energy support policy and a performance analysis of a grid connected 1 MWP PV power plant in Konya", Selçuk Üniversitesi Mühendislik, Bilim ve Teknoloji Dergisi, 5(3), 251-261.10.1115/1.4050376
  • Darbali-Zamora, R., Johnson, J., Summers, A., Jones, C. B., Hansen, C., & Showalter, C. (2021). "State Estimation Based Distributed Energy Resource Optimization for Distribution Voltage Regulation in Telemetry-Sparse Environments Using a Real-Time Digital Twin", Energies, 14(3). doi: ARTN 77410.3390/en14030774
  • Dhimish, M. (2021). "Defining the best-fit machine learning classifier to early diagnose photovoltaic solar cells hot spots", Case Studies in Thermal Engineering, 25. doi: ARTN 10098010.1016/j.csite.2021.100980
  • Jain, P., Poon, J., Singh, J. P., Spanos, C., Sanders, S. R., & Panda, S. K. (2020). "A Digital Twin Approach for Fault Diagnosis in Distributed Photovoltaic Systems", Ieee Transactions on Power Electronics, 35(1), 940-956. doi: 10.1109/Tpel.2019.2911594
  • Juarez, M. G., Botti, V. J., & Giret, A. S. (2021). "Digital Twins: Review and Challenges", Journal of Computing and Information Science in Engineering, 21(3). doi: Artn 03080210.1115/1.4050244
  • Kolantla, D., Mikkili, S., Pendem, S. R., & Desai, A. A. (2020). "Critical review on various inverter topologies for PV system architectures", Iet Renewable Power Generation, 14(17), 3418-3438. doi: 10.1049/iet-rpg.2020.0317
  • Kritzinger, W., Karner, M., Traar, G., Henjes, J., & Sihn, W. (2018). "Digital Twin in manufacturing: A categorical literature review and classification", Ifac Papersonline, 51(11), 1016-1022. doi: 10.1016/j.ifacol.2018.08.474
  • Lattanzi, L., Raffaeli, R., Peruzzini, M., & Pellicciari, M. (2021). "Digital twin for smart manufacturing: a review of concepts towards a practical industrial implementation", International Journal of Computer Integrated Manufacturing. doi: 10.1080/0951192x.2021.1911003
  • Lim, K. Y. H., Zheng, P., & Chen, C. H. (2020). "A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives", Journal of Intelligent Manufacturing, 31(6), 1313-1337. doi: 10.1007/s10845-019-01512-w
  • Liu, M. N., Fang, S. L., Dong, H. Y., & Xu, C. Z. (2021). "Review of digital twin about concepts, technologies, and industrial applications", Journal of Manufacturing Systems, 58, 346-361. doi: 10.1016/j.jmsy.2020.06.017
  • Lu, Y. L., Huang, X. H., Zhang, K., Maharjan, S., & Zhang, Y. (2021). "Communication-Efficient Federated Learning for Digital Twin Edge Networks in Industrial IoT", Ieee Transactions on Industrial Informatics, 17(8), 5709-5718. doi: 10.1109/Tii.2020.3010798
  • Moghadam, F. K., Reboucas, G. F. D., & Nejad, A. R. (2021). "Digital twin modeling for predictive maintenance of gearboxes in floating offshore wind turbine drivetrains", Forschung Im Ingenieurwesen-Engineering Research, 85(2), 273-286. doi: 10.1007/s10010-021-00468-9
  • Nguyen, V. H., Tran, Q. T., Besanger, Y., Jung, M., & Nguyen, T. L. (2021). "Digital twin integrated power hardware-in-the-loop for the assessment of distributed renewable energy resources", Electrical Engineering. doi: 10.1007/s00202-021-01246-0
  • ÖKSEL, C., Ali, K. O. Ç., Yıldız, K. O. Ç., & YAĞLI, H. (2016). "Off-shore Wind Energy Potential Research for Antakya Bay", Selçuk Üniversitesi Mühendislik, Bilim ve Teknoloji Dergisi, 4(1), 18-29.
  • Peng, Y. Z., Zhao, S., & Wang, H. (2021). "A Digital Twin Based Estimation Method for Health Indicators of DC DC Converters", Ieee Transactions on Power Electronics, 36(2), 2105-2118. doi: 10.1109/Tpel.2020.3009600
  • Rassolkin, A., Orosz, T., Demidova, G. L., Kuts, V., Rjabtsikov, V., Vaimann, T., & Kallaste, A. (2021). "Implementation of Digital Twins for electrical energy conversion systems in selected case studies", Proceedings of the Estonian Academy of Sciences, 70(1), 19-39. doi: 10.3176/proc.2021.1.03
  • Schroeder, G. N., Steinmetz, C., Rodrigues, R. N., Henriques, R. V. B., Rettberg, A., & Pereira, C. E. (2021). "A Methodology for Digital Twin Modeling and Deployment for Industry 4.0", Proceedings of the Ieee, 109(4), 556-567. doi: 10.1109/Jproc.2020.3032444
  • Sjarov, M., Lechler, T., Fuchs, J., Brossog, M., Selmaier, A., Faltus, F., Franke, J. (2020). "The Digital Twin Concept in Industry - A Review and Systematization", 2020 25th Ieee International Conference on Emerging Technologies and Factory Automation (Etfa), 1789-1796.
  • Sun, W., Lei, S. Y., Wang, L., Liu, Z. Q., & Zhang, Y. (2021). "Adaptive Federated Learning and Digital Twin for Industrial Internet of Things", Ieee Transactions on Industrial Informatics, 17(8), 5605- 5614. doi: 10.1109/Tii.2020.3034674
  • Uzum, B., Onen, A., Hasanien, H. M., & Muyeen, S. M. (2021). "Rooftop Solar PV Penetration Impacts on Distribution Network and Further Growth Factors-A Comprehensive Review", Electronics, 10(1). doi: ARTN 5510.3390/electronics10010055
  • Wang, M. M., Wang, C. Y., Hnydiuk-Stefan, A., Feng, S. Z., Atilla, I., & Li, Z. (2021). "Recent progress on reliability analysis of offshore wind turbine support structures considering digital twin solutions.", Ocean Engineering, 232. doi: ARTN 10916810.1016/j.oceaneng.2021.109168
  • Zohdi, T. I. (2021). "A digital-twin and machine-learning framework for the design of multiobjective agrophotovoltaic solar farms.", Computational Mechanics. doi:10.1007/s00466-021-02035-z
There are 27 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Review Article
Authors

Göksel Gökkuş 0000-0003-4266-5556

Publication Date September 1, 2021
Submission Date July 12, 2021
Acceptance Date August 4, 2021
Published in Issue Year 2021 Volume: 9 Issue: 3

Cite

IEEE G. Gökkuş, “DIGITAL TWIN CONCEPT FOR RENEWABLE ENERGY SOURCES”, KONJES, vol. 9, no. 3, pp. 836–844, 2021, doi: 10.36306/konjes.969989.